Mutation Assessor - Stomach Adenocarcinoma (Primary solid tumor)

Mutation Assessor

Stomach Adenocarcinoma (Primary solid tumor)

23 September 2013 | analyses__2013_09_23

Maintainer Information

Citation Information

Maintained by David Heiman (Broad Institute)

Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Mutation Assessor. Broad Institute of MIT and Harvard. doi:10.7908/C13X851V

Overview

Introduction

This report serves to summarize the functional impact of missense mutations in each gene as determined by Mutation Assessor[1].

Summary

High Functional Impact Missense Mutations: 4260
Medium Functional Impact Missense Mutations: 24056
Low Functional Impact Missense Mutations: 23657
Neutral Functional Impact Mutations: 17665

Results

Functional Impact by Gene

Table 1. Get Full Table A gene-level breakdown of missense mutation functional impact, ordered by MutSig rank. Includes missense mutation counts broken down by level of functional impact (high, medium, low, neutral), median functional impact score and level, and most common level(s) of functional impact (mode) per gene.

Gene	MutSig Rank	High Functional Impact Count	Medium Functional Impact Count	Low Functional Impact Count	Neutral Functional Impact Count	Median Functional Impact Score	Median Functional Impact Level	Mode Functional Impact Level
TRIM48	1	0	0	1	13	-0.6650	neutral	neutral
PIK3CA	2	0	24	26	11	1.6200	low	low
PGM5	3	0	19	4	0	2.9450	medium	medium
KRAS	4	2	20	3	0	3.2450	medium	medium
CBWD1	5	0	1	1	0	1.7400	low	medium/low
TP53	6	0	60	5	0	3.0000	medium	medium
ARID1A	7	0	7	7	2	1.7625	low	medium/low
SMAD4	8	6	10	0	0	3.4850	medium	medium
RHOA	9	4	9	1	0	3.1100	medium	medium
MXRA8	10	0	1	3	0	1.7475	low	low

Methods & Data

Input

STAD-TP.maf.annotated
STAD-TP.sig_genes.txt
Mutation Assessor Scores Release 2:

hg18
hg19

A lookup is done against the relevant Mutation Assessor Scores table for each missense mutation in a given MAF file, and available functional impact score and level are appended as two new columns to generate STAD-TP.maf.annotated. These are summarized in Table 1, sorted by MutSig rank.

Download Results

In addition to the links below, the full results of the analysis summarized in this report can also be downloaded programmatically using firehose_get, or interactively from either the Broad GDAC website or TCGA Data Coordination Center Portal.

References

[1] Boris Reva, Yevgeniy Antipin, and Chris Sander, Predicting the functional impact of protein mutations: application to cancer genomics, Nucl. Acids Res. 39(17):e118 (2011)

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